Integrated multi-omics network analysis reveals key metabolic pathways in gastric adenocarcinoma

Abstract

Abstract Gastric adenocarcinoma is one of the most death cause cancers worldwide. Metabolomics is an effective approach for investigating the occurrence and progression of tumors and detecting prognostic biomarkers by studying the profiles of small bioactive molecules. To fully decipher the functional roles of the disrupted metabolites that modulate the cellular mechanism of gastric cancer, integrated multi-omics network methods are critical to map the associations between metabolites and genes. In this study, we constructed a knowledge-based multi-omics network of gastric cancer using the dysregulated metabolites and genes between gastric cancer patients and healthy controls. Topological pathway analysis and gene-protein-metabolite-disease association analysis were conducted, and four key gene-metabolite pathways were identified including eleven metabolites associated with modulated genes. The integrated multi-omics network enables mechanistic investigation and provides a comprehensive overview regarding the investigation of molecular mechanisms of gastric cancer, which facilitates the in-depth understanding of metabolic biomarker roles in gastric cancer.